Current Trends in Information Technology vol 6 issue 3

(CTIT) ISSN 2249-4707 (Online) ISSN 2348-7895 (Print)

Current Trends in

INFORMATION TECHNOLOGY SJIF: 3.577

September–December 2016

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It is my privilege to present the print version of the [Volume 6 Issue 3] of our Current Trends in Information Technology, 2016. The intension of CTIT is to create an atmosphere that stimulates vision, research and growth in the area of Information Technology.

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Contents 1. Hadoop and Map Reduce for Simplified Processing of Big Data Shobha Rani

1

2. Big Data to Big Data Mining: Issues, Challenges and Data Analytics Solutions Neeraj Kumar, Madhulika Pandey, Krishan Kumar

7

3. Group Management for Secure and Dynamic Sharing of Data in Cloud Computing Raju Dara, Bhongir Sony

16

4. Public Auditing Based Detection of Packet Dropping Attacks in Wireless Ad Hoc Networks Raju Dara, Srikanth Ravula

24

5. Double Guard: Detection Intrusion in Multitier Application S.D. Jadhav, S.R. Nallewar, N.V. Burande, G.V. Bawaskar, R.D. Shilpakar

32

6. Protected Data Compilation in WSN Using Random Routing Algorithms Raju Dara, Jellela Satish Reddy

43

Current Trends in Information Technology

ISSN: 2249-4707(online), ISSN: 2348-7895(print) Volume 6, Issue 3 www.stmjournals.com

Hadoop and Map Reduce for Simplified Processing of Big Data Shobha Rani* Department of Computer Science, Akarapu Sharath Chandrika Devi Memorial College for Women, Warangal, Telangana, India Abstract

Big data refers to large and complex data sets made up of a variety of structured and unstructured data, which are too big, too fast, or too hard to be managed by traditional techniques. Hadoop is an open source software platform for structuring big data on computer clusters built from commodity hardware and enabling it for data analysis. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. MapReduce is a programming model for processing large data sets with parallel distributed algorithm on cluster. This paper presents the survey of simplified big data processing with Hadoop architecture and MapReduce framework.

Keywords: Big data, Hadoop, MapReduce, HDFS, Big data Analytics

INTRODUCTION

Currently, enormous amounts of data are created every day. With the rapid expansion of data, we are moving from the terabyte to the petabyte Age. At the same time, new technologies make it possible to organize and utilize the massive amounts of data currently being generated. However, this trend creates a great demand for new data storage and analysis methods [1, 2]. Especially, theoretical and practical aspects of extracting knowledge from massive data sets have become quite important.

The term “Big Data” has recently been applied to datasets that grow so large and become unsuitable to work with the traditional database management systems. They are data sets whose size is beyond the ability of commonly used

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software tools and storage systems to capture, store, manage, as well as process data within a tolerable elapsed time [3]. Big data sizes are constantly increasing, currently ranging from terabytes to petabytes of data in a single data set. Consequently, some of the problems related to big data include data capture, store, searching, sharing, analysis and visualization.

Today enterprises are exploring large volumes of highly detailed data so as to discover facts they did not know before [4].  Ambiguity—a lack of metadata creates ambiguity in big data that leads to inconsistency (Figure 1).  Viscosity—measure of data flow over the network.

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ISSN: 2249-4707(online), ISSN: 2348-7895(print) Volume 6, Issue 3 www.stmjournals.com

Big Data to Big Data Mining: Issues, Challenges and Data Analytics Solutions Neeraj Kumar, Madhulika Pandey*, Krishan Kumar Department of Computer Science, JIMS Engineering Management Technical Campus, Greater Noida, Uttar Pradesh, India Abstract

Data has evolved at a great pace due to increasing interest of people and valuable contribution towards the emerging technologies. Emerging technologies are successful in generating huge quantity of data from various sources which in return provides Big Data. Big Data constitutes large amount of data in terms of texts, statistics, facts, figures, and records, etc., generated from heterogeneous environment. Big Data needs special attention for storage, managing, transportation and processing of data. It includes amassing of data in terms of 3V’s, i.e. volume, variety and velocity. Issues and challenges of Big Data are real time obstacles and needs instant consideration. This paper presents the overview of Big Data along with its issues and challenges. Applications of data mining in Big Data along with some of its open sources are also discussed in the paper.

Keywords: Big Data, big data analytics, big data mining, Massive Online Analysis, R, GraphLab, Pegasus, Mahout

INTRODUCTION

million videos every minute [2]. Applications of internet, such as E-commerce, social networking sites, etc., are speeding up the data generation process, this type of data generated and gathered in huge volume is ‘Big Data’.

Big Data is making its valuable place in global economy as it is turning into driving force for economy. As data is increasing day by day, so with the increase of size of data it is difficult to manage such huge volume with the current technology. Data is collected from various sources because of which it is heterogeneous in nature and may be deficient as well. There is a need to store, manage and process the data with innovative technology that can handle and make use of data and transform it into meaningful data, i.e. information.

The data volumes are exploding. Today, more than 2.5 exabytes (2.5 billion gigabytes) of data is generated every single day. This is expected to continue growing at a significant rate with mobile devices accounting for much of this data. Every second we create new data.

For example, we perform 40,000 search queries every second (on Google alone), which makes it 3.5 searches per day and 1.2 trillion searches per year. Facebook users send on average 31.25 million messages and view 2.77

This information from data is analyzed using new techniques for generating valuable outcomes useful for organizations and businesses (Figure 1). This holds importance in knowledge discovery and decision support system. The data management of Big Data is beyond the capability of classic database or computer system. Big Data Analytics are the one who generates valuable outcomes from

In the pre-digital revolution world of the late 1980s, most of the data was stored on videotapes such as VHS cassettes, Vinyl LP records, audio cassette tapes, and photography accounted for significant portions as well.

Paper based storage represented 33% of all the data storage on its own in 1986. 25 % of all the data stored in the world in 2000 was stored digitally. 2002 was the first year in which digital storage capacity overtook analog capacity. The digital storage grew annually by 23% between 1986 and 2007 with 94 % of all the data was stored in digital format by 2007 [1]. Now, we are successful in generating and collecting data from numerous sources.

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ISSN: 2249-4707(online), ISSN: 2348-7895(print) Volume 6, Issue 3 www.stmjournals.com

Group Management for Secure and Dynamic Sharing of Data in Cloud Computing Raju Dara, Bhongir Sony* Department of Computer Science Engineering, Krishna Murthy Institute of Technology and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India Abstract

Cloud computing has emerged as new model of computing which allows outsourcing data.

The phenomenon of outsourcing data to cloud became obvious as cloud has infrastructure as a service (IaaS) layer for it. With this feature of cloud, there is growing trend in outsourcing data to cloud. When an enterprise outsources its data to cloud, it needs to take care of its functionalities in terms of data sharing across its users. The company creates groups and manages group members in order to have secure and dynamic data sharing. Group manager is responsible to determine data to be shared and privileges of group members. Group management is very dynamic thing where new users may be added and existing members may be removed from group. The users who are not associated with the group may involve in collusion attack. The existing systems focus on group management and data sharing. In this paper, we built a mechanism for revoking a user and disable all credentials given to him. We built a prototype application that demonstrates the proof of concept. The empirical results revealed that the proposed scheme is effective.

Keywords: Cloud computing, outsourcing, group management, secure data sharing, user revocation

INTRODUCTION

Cloud computing became a reality. This is in fact the latest technology that enables the world to have a shared pool of resources and access the resources through internet. This phenomenon works for users without making capital investment. The users of cloud can gain access to resources and pay as they use. This is very useful to computing community as the cloud resources are made available to all without restrictions. As the data is growing exponentially, the enterprises prefer outsourcing data to cloud for reducing expenses and ease of management. However, the cloud is treated as untrusted environment.

That is the reason there is security concern while outsourcing data to cloud. Cloud can also be used to store and share data to other users. Cloud services are shown in Figure 1.

In this context, the data may be associated with different groups in the cloud assuming that an enterprise has multiple groups of people working on different projects. In this case, data is associated with groups. The data

of one group is not accessible to other group.

There is group manager who is responsible to manage data and group members. Group members may be added or removed as required. The group manager is responsible to handle security issues also. Group manager can grant or remake privileges to group members. The problem with such system is that when users are removed from the group, their access credentials are misused by people to make collusion attacks. In this paper, we proposed a user revocation scheme that takes care of perfect user revocation process. With user revocation, it is possible that the old credentials cannot be misused and thus the collusion attack is prevented. In this paper, our contribution is to have a secure and dynamic scheme for data sharing in cloud and it is equipped with user revocation scheme for complete security. The remainder of the paper is structured as follows: next part of the paper provides review of literature. After that, the proposed system is presented in detail, followed by experimental results and the conclusion.

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ISSN: 2249-4707(online), ISSN: 2348-7895(print) Volume 6, Issue 3 www.stmjournals.com

Public Auditing Based Detection of Packet Dropping Attacks in Wireless Ad Hoc Networks Raju Dara, Srikanth Ravula* Department of Computer Science Engineering, Krishna Murthy Institute of Technology and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India Abstract

Wireless ad hoc networks are vulnerable to packet dropping attacks. However, they are also subjected to packet dropping due to link errors. In case of multi-hop wireless networks, it is essential to differentiate packet dropping due to link error or malicious attack. When any mechanism is able to differentiate this, can provide high level of security to the network with respect to packet dropping attacks. Many solutions came into existence as found in the literature. In this paper, we considered a special insider attack where malicious nodes are aware of other nodes in the network and exploit their knowledge to achieve packet drop which is potential risk in communication networks. Achieving satisfactory accuracy in detection of packet loss due to malicious attacks is given high importance. In this paper, public auditing mechanism is proposed and implemented that exploits correlations between lost packets. We proposed a public auditing architecture for accurate detection of packet drop attacks. We built a custom simulator using Java platform to demonstrate the proof of concept. The empirical results reveal the usefulness of the proposed system.

Keywords: Wireless ad hoc network, packet dropping, auditing

INTRODUCTION

Network is made up of number of nodes. Each node in the network can act as information sender and information receiver. It is true in case of multi-hops between sender and receiver. The sender may not be able to send packets directly to destination without the cooperation from intermediate nodes on the way. Therefore, it is essential to have such cooperation. Having understood this, there are certain issues here. The intermediate nodes may act as malicious nodes and drop packets without forwarding to neighbours.

In wireless ad hoc networks, this is the problem that needs to be addressed. As packets play a vital role in communication, dropped packets cannot provide meaningful information to destination. This way the communication quality is deteriorated. With respect to delay, insensitive packets pertaining to a live event, it is important to ensure that packets are reaching destination accurately.

Thus there is need for dealing with this problem in order to have meaningful communications in communication networks.

The existing applications either focused on packet dropping caused by link errors or attacks. Many existing mechanisms simply consider packet dropping due to attacks. They do not differentiate packet loss due to link error and packet loss due to an attack. In this paper we proposed a public auditing based solution, which demonstrates the proof of concept. The system is implemented in the form of a custom simulator developed using Java platform. The empirical results revealed that the proposed system is able to differentiate between packet losses due to link error from that caused by malicious attacks.

The remainder of the paper is structured as follow: next part of the paper provides review of literature, presentation of the proposed system in detail, experimental results and after that, the conclusion of the paper.

RELATED WORKS

Malicious packet drops and packet drops due to link errors is the differentiation shown by detection algorithms generally. High malicious dropping rates and low link errors in one pattern. The second pattern is high link errors

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ISSN: 2249-4707(online), ISSN: 2348-7895(print) Volume 6, Issue 3 www.stmjournals.com

Double Guard: Detection Intrusion in Multitier Application S.D. Jadhav*, S.R. Nallewar, N.V. Burande, G.V. Bawaskar, R.D. Shilpakar Department of Information Technology, Dhole Patil College of Engineering, Wagholi, Pune, Maharashtra, India Abstract

In double guard intrusion in multitier system, it is important concept taking into account attacks. There is very little work being performed on multi-tiered anomaly detection (AD) systems. It generates models of network behavior for both web and database network interactions. In such multi-tiered architectures, the back-end database server is often protected in system behind a firewall, while the web servers are remotely over the internet.

Though they are protected from direct remote attacks, the back-end systems are susceptible to attacks that use web requests as a means to exploit. It detects this type of attack since the web IDS would merely see typical user login traffic. The current multi-threaded web server architecture in this system carries multiple systems; it is not feasible to detect or profile such causal mapping between web server traffic and it has deserver traffic, since traffic cannot be clearly attributed to user sessions in the use.

Keywords: Attacks, double guard, IDS, SQL, TCP

INTRODUCTION Problem Definition In this project we present double guard, a system used to detect various attacks in multitiered web services and our approach can create normality models of isolated user sessions that include both, the web front end (HTTP) and back end (File or SQL) network transactions [1]. To achieve this, we employ a lightweight virtualization technique to assign each user’s web session to addicted container, an isolated virtual computing environment.

We use the container ID to accurately associate the web request with the subsequent DB queries. Double guard can build a causal mapping profile by taking both, the in web server and DB traffic into account in the system used [2].

Objective Intrusion detection system currently examines network request individually within both, the web server and the database system. However, there is very little work being performed on multi-tiered anomaly detection systems that generate models of network behavior for both, back end and web server database interactions.

The back end database server is often protected

behind a firewall while the web servers are remotely accessible over the internet. Attacks that use web request as a means to exploit the back end and are very important.

Need of Project Attacks like Sql and DDoS are very much severe. These attacks in the past have affected the system many number of times. These types of attacks are not recognized by antivirus or by firewalls. Hence, a system that can recognize and deflect these attacks is required.

LITERATURE SURVEY

Of all the papers referred to implement the proposed system, systems similar to the one proposed here and on which we attempt to present improvements on, can be espied in three of the research papers [1–3].

We have successfully applied static program analysis to intrusion detection and our approach is automatic: the programmer or system administrator merely needs to run our tools on the program at hand. All other automatic approaches to intrusion detection to date have been based on statistical inference, leading to many false alarms; in contrast, our

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Protected Data Compilation in WSN Using Random Routing Algorithms Raju Dara, Jellela Satish Reddy * Department of Computer Science Engineering, Krishna Murthy Institute of Technology and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India Abstract

Wireless sensor networks make it conceivable to send secure information from source to destination. On the off chance that connected to network checking information on a host, they can be used to distinguish bargained hub; and refusal of administration is two-key assault. In this paper, we display four "Multi-way randomized directing Algorithm", a technique to send the information, various approaches to order the information into wireless sensor systems.

The pure random propagation, shares are engendered in view of one-bounce neighborhood data, sink TTL beginning worth N in every offer and remaining calculations enhance the effectiveness of shares in light of utilizing two-jump neighborhood data. Our work ponders the best calculation by distinguishing the included hubs with dark gaps and refusal of administration in the bundle data with multipath directing calculations that has not been utilized some time recently. We investigated the calculation that have the best proficiency and depicts the proposed framework.

Keywords: Wireless sensor networks, security, attacks and routing

INTRODUCTION

Wireless sensor networks normally comprise of high cost, low-control, and multifunctional wireless sensor hubs, with detecting wireless correspondence capacities [1, 2]. These sensor hubs impart the separation by means of a wireless medium and work together to fulfill a typical undertaking, for instance, environment checking, military reconnaissance, and mechanical procedure control (Figure 1) [3].

The fundamental reasoning behind WSNs is that, while the ability of every individual sensor hub is constrained, the total force of the whole system is adequate for the required mission.

In numerous WSN applications, the organization of sensor hubs is performed in an especially appointed manner without watchful arranging and designing. Once sent, the sensor hubs must have the capacity to self-ruling, and sort out themselves into a wireless correspondence system. Sensor hubs are battery-controlled and are relied upon to work without participation for a generally drawn out stretch of time.

Most of the time it is extremely troublesome and even difficult to change or revive batteries for the sensor hubs. WSNs are portrayed with

denser levels of sensor hub, lack of quality of sensor hubs, and separate force, calculation, and memory limitations. In this way, the kinds attributes and requirements present numerous new difficulties for the advancement and use of WSNs. Wireless sensor system (WSN) is a heterogeneous framework joining a large number of small, modest sensor hubs with a few recognizing qualities. It is low handling force and radio reaches, allowing low vitality utilization in the sensor hubs, and performing constrained and particular detecting and observing capacities [1–6].

Notwithstanding WSNs structure, a specific class of specially appointed systems that work with little base and have pulled in scientists for its improvement and numerous potential regular citizen and military applications, for example, ecological observing, combat zone reconnaissance, and country security. Be that as it may, outlining security conventions is a

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Current Trends in

INFORMATION TECHNOLOGY SJIF: 3.577

September–December 2016

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